Data Engineer

Data is a core pillar of SCOR’s Forward 2026 strategic plan and beyond. Our ambition is to enable trusted, governed, and accessible data so that business teams can generate insights faster and make better decisions.

As a Data Engineer within the Chief Data Officer organization, you will design and deliver analytics and AI ready datasets and curated data products that power dashboards, reporting, and analytical use cases within one primary business domain: Property & Casualty, Life & Health, or Finance.

A critical aspect of this role is a strong understanding of the business domain you are supporting. You are expected to develop deep knowledge of key processes, metrics, and decision drivers within your assigned domain, and to translate this business understanding into robust analytical data models, consistent KPIs, and meaningful datasets.

Increasingly, analytical use cases at SCOR are augmented by AI‑driven capabilities. As such, this role assumes that the candidate understands and has practical experience working with AI agents or AI‑assisted analytics (e.g. agents supporting data exploration, metric analysis, automation, or decision support). The Data Engineer is expected to leverage these capabilities thoughtfully to accelerate insight generation, improve usability of analytical datasets, and enhance business decision‑making.

You will work at the intersection of data engineering and analytics, shaping data models, implementing transformations, ensuring data quality, and making datasets discoverable and usable for business consumers on SCOR’s enterprise data foundation (Genesis) and modern data platforms.

The Data Engineer is a professional who is:

• Outcome‑driven: Focuses on delivering datasets and metrics that materially improve business steering and decision‑making (timeliness, trust, usability). 

• Data‑product minded: Treats analytical datasets as products with clear contracts (definitions, grain, lineage, quality expectations, documentation).

• Quality & governance oriented: Designs datasets that are consistent, auditable, and aligned with governance expectations (definitions, controls, traceability).

• Collaborative bridge‑builder: Works effectively with business stakeholders, Data Foundation, Governance, Analytics & AI, and Platform teams to translate needs into robust analytical assets.

• Clear communicator: Can explain complex data concepts in a practical way and build trust with both technical and non‑technical stakeholders.
   

As a leading global reinsurer, SCOR offers its clients a diversified and innovative range of reinsurance and insurance solutions and services to control and manage risk. Applying “The Art & Science of Risk,” SCOR uses its industry-recognized expertise and cutting-edge financial solutions to serve its clients and contribute to the welfare and resilience of society in around 160 countries worldwide.

Working at SCOR means engaging with some of the best minds in the industry – actuaries, data scientists, underwriters, risk modelers, engineers, and many others – as we work together to find solutions to pressing challenges facing societies.

As an international company, our common culture is defined by “The SCOR Way.” Serving both to build momentum that drives the Group forward and as a compass to guide our actions and choices, The SCOR Way is anchored by five core values, reflecting the input of employees at all levels of the Group. We care about clients, people, and societies. We perform with integrity. We act with courage. We encourage open minds. And we thrive through collaboration.

SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.